Autonomous and Adaptive Systems 2021-22
The goal of this module is to provide a solid introduction to the design of autonomous and adaptive computing systems from a theoretical and practical point of view. Topics will include principles of autonomous system design, reinforcement learning, game-theoretic approaches to cooperation and coordination, bio-inspired systems, complex adaptive systems, and computational social systems. The module will also cover several practical applications from a variety of fields including but not limited to distributed and networked systems, mobile and ubiquitous systems, robotic systems, and vehicular and transportation systems.
Link to official course page containing syllabus and textbooks
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Intelligent Agents and Machines
Introduction to Reinforcement Learning
Introduction to Multi-Armed Bandits
Introduction to Deep Learning - First Part
Introduction to Deep Learning - Second Part
Introduction to Deep Learning - Third Part
Introduction to TensorFlow and Keras
Introduction to RL in TensorFlow - Advanced Topics
Autonomous Robots and Self-driving Cars
Last updated: 7 April 2022.